There is no separation method without a stationary phase. A description of the stationary phase properties in terms of a series of numerical descriptors is of essential importance and is a mandatory condition for the stationary phase identification, application of retention data banks, prediction of the retention behaviour, optimization of separation systems and development of new separation systems based on an adaptive methods.

Different approaches(1-4) have been used for description of the stationary phase properties ranging between theoretically based approaches and purpose-oriented tests. In spite of its importance, a general model for quantitative description of the GC stationary phase properties has not yet been not established.

Nowadays, the most common systems of stationary phase property characterization are based on application of tests resulting in a specification of the retention behaviour of a certain number of solutes, but not yielding numerical descriptors of the test stationary phase. The properties found in this way may differ when a different set of solutes is used to test the same stationary phase. These facts have given rise to numerous objections and discussions, see e.g.(5-14). The tests are thus dedicated to a particular purpose and hinder attempts at creating transferable data banks of the retention data and development of new chromatographic expert systems.

A general classification system should be able to quantitatively describe the properties of stationary phases in terms of their potential in weak interactions, inter-interactions and their effects on the retention. Such classification system should be thermodynamically based and should allow a prediction of the stationary phase properties based on their chemical structure.

We paid attention to four models of stationary phase classification. The models used were those of Rohrschneider(1), McReynolds(2)

, Ševèík(3) and Abraham(4). Standard solutes (48 compounds) have been selected according to Li, Zhang,Carr(15) in such a way that all the compounds used in the original works were included and the solutes for the solvation model had to fulfil a two-level factorial approach. Stationary phases of different chemical compositions have been examined over a temperature range from 60 to 120ºC. The evaluation has been carried out separately for all the four models, especially from the point of view of their inter-correlation, physico-chemical meaning and applicability.

It has been demosntrated that the solvation model is best suited for description of the properties of the examined stationary phases in the given temperature range, that it specifies the fraction of week interactions responsible for the retention in terms of the values of the regression parameters of the solvation equation. Furthermore, the regression parameters of the solvation equation can be linked to a defined type of week interaction.

It can be shown that regression parameter l , describing dispersive interactions, is predominant for poly-dimethylsiloxane and poly-diphenyldimethylsiloxane stationary phases, while parameter s , describing dipolarity-polarizibility, is larger for poly-diphenyldimethylsiloxane stationary phases, because of the phenyl group. Similarly, the basicity, expressed by parameter a , is largest for poly-ethyleneglycol, while the acidity, expressed by parameter b , is largest for poly-bis-cyanopropylsiloxane. It has been found that the temperature dependence of the regression parameters l, r, s, a, b of the solvation equation is in agreement with decreasing inter-molecular interactions. It has been found that all the investigated models for the stationary phase properties description are highly correlated, R2 > 0.95 and significantly (F>3000) linked through dispersive interactions expressed by parameter l (4) and criteria A(3) and B(1).

It can be concluded that stationary phase characterization by a set of numerical descriptors, such as regression parameters l, r, s, a, b of the solvation equation(4), which are linked with a defined type of week interaction, can serve as a general approach to stationary phase characterization and, consequently, can lead to development of new GC instrumentation toward expert systems.